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Deadline for Manuscript Submission:
December 30, 2021

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Call for Papers

Special Issue: Big Data-Driven Futuristic Fabric System in Societal Digital Transformation


Guest Editors

Dr. Chinmay Chakraborty (Leading Guest Editor)
Department of Electronics and Communication Engineering
Birla Institute of Technology, Mesra, India
Email: cchakrabarty@bitmesra.ac.in 

Prof. Muhammad Khurram Khan
King Saud University, Kingdom of Saudi Arabia
Email: mkhurram@ksu.edu.sa   

Prof. Ishfaq Ahmad
University of Texas at Arlington, USA
Email: iahmad@cse.uta.edu  
 

Big data-driven futuristic fabric system (B_FFS) is the most immersive technological solutions that give seamless, real-time integration, and massive data access across the diverse big data sources using artificial intelligence, Internet of Things (IoT), information science, statistics, pattern recognition, collaborative learning, database, security, cognitive technologies, knowledge acquisition, and data visualization technology. Society is endlessly upgrading with a faster way under digital transformation using digital communication and infrastructures. The B_FFS consists of data access, discovery, orchestration, ingestion, processing, management, and intelligence. 

The B_FFS is continuously gathering digital social data in high-velocity, high-volume, and high-variety from computer-based communications and social media interactions. The B_FFS datasets having massive user information. The process of B_FFS consists of three stages like data acquisition; data mining; and data validation. An intelligent B_FFS improves the business decision support process by extracting meaningful user information from different sources. The information is coming from the various sources via sensors used to accumulate traffic, health, weather, transportation data, and posts to various social media sites. 

This special issue focuses on the recent development of B_FFS for increasing the massive data integration in a single platform smoothly and intelligently. Thus, we here are seeking the most impactful and newest findings on how to process and visualize the B_FFS using emerging Artificial intelligence/computational intelligence in the Internet of Things. 

Topics of Interest
This special issue seeks original unpublished papers focusing on theoretical analysis, emerging applications, novel system architecture construction and design, experimental studies, and social impacts of big social data analytics and visualization services. Topic areas include, but are not limited to, the following

  • Health, transportation, traffic information processing in B_FFS
  • Digital Communications and Digital Transportation for IoT-B_FFS
  • Collaborative learning-assisted B_FFS management
  • Health, transportation, traffic information processing in B_FFS
  • AI-enabled B_FFS service management 
  • Decision support systems and ontology for B_FFS
  • Digital Buildings and Digital Factory for B_FFS
  • Digital Twins, Digital Identity, Digital Culture for B_FFS
  • Big data leakage resilient methodologies for B_FFS
  • Data leakage detection from Cloud, edge, fog, IoT, or Mobile applications
  • Semantic web and Data mining for B_FFS
  • Multimedia B_FFS analytics
  • Digital Misinformation and Fake News for B_FFS
  • Computational intelligence in remote B_FFS analytics
  • Complex social data analysis for B_FFS
  • Robust optimization techniques for B_FFS analytics 

Deadline of Submissions: December 30, 2021


Submission Guidelines
Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. Paper submissions for this special issue should follow the submission format and guidelines. Paper submissions for this special issue should follow the submission format and guidelines.
 

Learn More about this journal

Deadline for Manuscript Submission:
December 30, 2021

SUBMIT YOUR MANUSCRIPT